Goat systems of Villuercas-Ibores area in SW Spain: Problems and perspectives of traditional farming systems

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Small Ruminant Research 97 (2011) 1–11

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Small Ruminant Research

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Goat systems of Villuercas-Ibores area in SW Spain: Problems andperspectives of traditional farming systems

P. Gaspara,∗, A.J. Escribanob, F.J. Mesíasc, M. Escribanob, A.F. Pulidoc

a Departamento de Producción Animal y Ciencia de los Alimentos, Escuela de Ingenierías Agrarias, Universidad de Extremadura,Ctra. Cáceres s/n, Badajoz, Spainb Departamento de Producción Animal y Ciencia de los Alimentos, Facultad de Veterinaria, Avda. Universidad s/n, Cáceres, Spainc Departamento de Economía, Escuela de Ingenierías Agrarias, Universidad de Extremadura, Ctra. Cáceres s/n, Badajoz, Spain

a r t i c l e i n f o

Article history:Received 30 April 2010Received in revised form 28 February 2011Accepted 2 March 2011Available online 23 March 2011

Keywords:Goat systemsFarm typologyPDO “Ibores Cheese”Multivariate analysisManagement practices

a b s t r a c t

A study of dairy goat systems was carried out in the “Villuercas-Ibores” region, a mountain-ous area located in the south-west of the Iberian Peninsula (Cáceres, Spain). This territoryis characterized by difficult orography and a fairly harsh climate, and has low indices ofincome and population density. Goat production in the area has contributed notably toits economic and social development historically, but there has been a marked recessionin goat-based activities in recent decades, leading to changes in the type and intensityof land use. The purpose of the study is to analyze the main characteristics of the cur-rent goat farming systems in a zone in which goat milk production is possible under aProtected Designation of Origin (PDO) brand “Ibores Cheese”, and to establish a farm clas-sification that will allow groups of holdings with common characteristics to be identified,so that they can be compared and their performance evaluated. The data were obtainedthrough direct interviews to goat farmers (n = 61) within the geographical area of the PDO“Ibores Cheese”. Specific information on management was collected, together with data onfamily characteristics, labour, livestock numbers, land use, installations, continuity, recentchanges in farming, and the farmer’s opinions. A principal component analysis (PCA) wasused to examine the relationships among the quantitative variables, then a two-step clusteranalysis was applied using the factors obtained in the PCA and categorical variables. Thisresulted in a farm typology of three groups distinguished by their land use, goat breed, andPDO membership. The best management practices and productivity results were obtainedby the farms furthest removed from the traditional systems. The first group of farms is char-acterized by small size flocks. Many of these farms do not belong to the PDO and thereforethey have chosen breeds that are not allowed by the PDO regulations. Most of them aresemi-intensive or intensive farms. The second group consist of extensive farms with largesize flocks of goats complemented with sheep farming and, occasionally, with beef cattleor Iberian pig. They have got technically suitable milking rooms, although the availabilityof other infrastructure is poor. Finally, the third group identified includes extensive farmswhose goat flock size is very similar to that of group 1, but in 70% of the cases they are

mixed farms, mainly combining goat with sheep flocks. Most of them are producing milkthat is sold to firms producing PDO cheese. It is the group closest to the traditional farmingsystem and the farms have small flocks of low productivity per goat, raising autochthonousbreeds and their crossbreeds.

© 2011 Elsevier B.V. All rights reserved.

∗ Corresponding author. Tel.: +34 924286200; fax: +34 924272208.E-mail address: [email protected] (P. Gaspar).

0921-4488/$ – see front matter © 2011 Elsevier B.V. All rights reserved.doi:10.1016/j.smallrumres.2011.03.001

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1. Introduction

Historically, goat production has been linked toself-sufficiency (Morand-Fehr et al., 2004), and it has con-tributed to the economic and social development of poorrural areas and developing countries in which most of theworld’s goat population is concentrated. The versatility ofthe species, highly adapted to less-favoured areas, and thediversity of its production systems explain the continuinggrowth of the sector worldwide, with a 19% increase in thenumber of animals in the last decade (FAO, 2010).

Europe has not followed this growing trend, as its goatpopulation has decreased by 5.5% over the same period(FAO, 2010). This reduction has mainly been linked to thecontinued decline of rural areas. Even so, goat production inEurope is one of the livestock sectors with good economicprospects, as it is viewed as compatible with the sustain-able development and nature conservation promoted bythe new Common Agricultural Policy (CAP). Moreover, itis a sector that helps to fix rural population, reducing therisk of depopulation of marginal or less-favoured areas(Boyazoglu et al., 2005; Canali, 2006; De Rancourt et al.,2006) and contributing to the maintenance of good agri-environmental practices (MARM, 2008).

Spain, with 22% of the total EU goat census (13.5 mil-lion animals), occupies second position just after Greece(39.8%), according to data from 2007. Both countries havebeen losing relative importance within the EU due to newcountries joining the EU in the last few years. The mainraised breeds are autochthonous, including Murciano-Granadina, Majorera and Malaguena.

The number of farms amounts to 74,300, with an aver-age of 40 animals per farm, and a significant increase infarms devoted to dairy production (+7.1%). In 2009, pro-visional data show a slight decrease (1.8%) of the Spanishcensus, with a total of 2,906,517 goats. The evolution of thegoat population has experienced significant changes as aresult of goat milk price fluctuations (MARM, 2009).

The main goat producing areas in Spain are locatedin the southern half of the Iberian Peninsula and in theCanary Islands. When analyzing the production systems,we can find two different productive orientations: on theone hand the intensive farms that predominate in Andalu-sia and the Canary Islands; they raise dairy type breeds suchas Murciano-Granadina, Majorera and Malaguena, and theanimals are permanently confined. On the other hand wefind other “more extensive” farms, using dual purposebreeds for meat-milk production. Among these systemsthere are farms on which goats graze year-round, especiallyin mountainous areas, and others on which goats graze onlywhen forage is abundant (Castel et al., 2010).

A literature review showed several recent systemicanalyses of goat production from different perspectives.Some of the most noteworthy are the following. Paz et al.(2008) study the diversity of traditional goat systems.Castel et al. (2003) and Ruiz et al. (2008) characterize goat

farms in southern Spain using multivariate statistical meth-ods. Usai et al. (2006) characterize Sardinian goat farmingsystems, also using multivariate analysis, and taking intoaccount productive and breeding aspects of the farms. Goatproduction has also been studied from other perspectives,

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such as the influence of diet on production (milk or meat)(Ben Salem and Smith, 2008; Fedele et al., 2005; Galinaet al., 2007; Morand-Fehr et al., 2007), and breeding man-agement (Zarazaga et al., 2005).

One example of traditional goat farming systems isrepresented by those located in a mountainous region ofSW (SouthWest) Spain denominated “Villuercas-Ibores”(Fig. 1). This territory has low income indices and a verylow population density, both of which are linked to thedifficult orography which allows the use of modern agri-cultural and husbandry techniques in only a few specificareas. Nevertheless, it has a major diverse environmentalrichness, with several Natural Areas protected under Euro-pean Union regulations. Historically, goat production hascontributed remarkably to the economic and social devel-opment of this rural region, but there has been a markedrecession in the sector during the last two decades whichhas given rise to changes in the type and intensity of landuse. There is a Protected Designation of Origin (PDO) for thecheeses produced in this area, “PDO Ibores Cheese”, whichwas aimed at supporting the goat sector and improvingfarm revenues.

Protected Designation of Origin (PDO) is one of themost important programmes designed by the EuropeanUnion to promote and protect the names of regional foods.These programmes encourage varied agricultural produc-tion, protect the trademark of the PDOs and help consumersby giving them information concerning specific productcharacteristics. Specifically, PDO covers agricultural prod-ucts and foodstuffs which are produced, processed andprepared in a given geographical area. Such is the caseof the Ibores Cheese PDO, that was created in 2005. Thecheese produced under this PDO is a fatty cheese, madeexclusively from raw goat milk from the breeds Serrana,Verata, Retinta and their crossbreeds. Cheese ripening lastsat least 60 days, and after the ripening the cheese musthave a cylindrical shape, ivory color and semi-soft tex-ture and aroma. DOP rules state that cheese must containa minimum of 45% fat and 30% protein on dry matter,a pH of 5.0–5.5, and 4% NaCl or less. According to datafrom the PDO Regulatory Council, 2007 production was150,000 kg of cheese, that accounted for a turnover ofD1,560,000.

The “Villuercas-Ibores” goat sector has an interestingfuture due to the increasing demand for traditional and nat-ural products, and since its successful continuation goeshand-in-hand with the conservation of a highly-valuednatural environment. This aspect is specifically supportedby the European Union’s new policies. The PDO andregional foods have the potential to leverage wider socialand economic benefits (Ventura and Milone, 2000), as theyrepresent potentially fruitful resources for development(Marsden et al., 2000). They can also confer market-ing benefits and can contribute to the socio-economicwell-being of rural areas (Tregear et al., 2007) as theyhave the ability to attract consumers (Marescotti, 2003).

Nevertheless, and to reach these benefits, it is also nec-essary to improve consumer information (Mesias et al.,2003).

Given this context, and based on knowledge of themain features of traditional goat systems in “Villuercas-

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goat farmers who had more than 100 goats on their holdings, which gavea population of 161 goat farmers, with 50,683 goats. Among these farm-ers, 61 were selected randomly. The survey interviews were conductedon site, with the interviewee being the farm holder or the manager.

Fig. 1. Location of t

bores”, the objective of the present study was to establishtypology of its goat farms. This would allow one to ana-

yze possible problems of the different farm types, and toesign policies appropriate for each group (Benedict et al.,944). The construction of livestock farm typologies is aopic of burgeoning interest in livestock farming systemsesearch. These typologies are constructed for a variety ofurposes: (a) to evaluate changing trends in livestock farm-

ng; (b) to identify the main constraints on productivity orhe main priorities for a specific development policy; (c)s a basis for identifying “target groups” in developmentrojects; and (d) as a support tool for advisers workingith individual farmers, allowing them to assess a given

ituation by reference to known functional types (Gibon,994).

Multivariate statistical tools have become a proven andffective method of generating farm typologies from tech-ical and economic data (Gibon et al., 1999). The literatureeview showed that various farm typologies have beenonstructed using these techniques, usually based on struc-ural and production livestock variables (Castel et al., 2003;aspar et al., 2007, 2008; Milán et al., 2003; Serrano et al.,004a,b; Usai et al., 2006), but also on economic and soci-logical variables (Solano et al., 2000; Saïri and Lyoubi,003).

. Materials and methods

.1. Study area description

The study area is the Region designated “Villuercas-Ibores” in SWpain, of 1483.3 km2 area and 10 354 inhabitants. It is located in theutonomous Community of Extremadura between the Rivers Tagus and

rcas-Ibores region.

Guadiana, and takes its name from the surrounding mountains. It hasa mountainous topography, with a maximum height at the Pico de laVilluerca Alta (ca. 1600 m a.s.l.).1

The landscape is mainly that typical of Mediterranean forest, with apredominance in the foothills of the “dehesa” agroforestry system basedon holm and cork oak, and mountain forest at greater altitudes. Theclimate is continental Mediterranean, with annual mean temperaturesaround 15 ◦C, and mean annual rainfall of 1030 mm. The summers arelong, hot, and dry: the mean temperature of July is usually over 26 ◦C. Thewinters are normally mild with a mean temperature of 7.2 ◦C (Paniaguaet al., 2009).

It has a varied fauna, with the large fauna being deer, wild boar, cat-tle, and sheep. The endangered and iconic Iberian lynx is also found insome of the best preserved areas. It has been declared a Special ProtectionArea (SPA) for birds as it is a temporary place of residence and migratorystopover.

The goat census in these territories in 2005 was 57,619 head (CAYDR,2007). The main breeds are autochthonous Serrana, Verata, and Retinta,together with their crosses. Only these breeds may produce milk for PDO“Ibores Cheese”.

2.2. Data collection, questionnaire design, and statistical analyses

The data were obtained through direct survey interviews with goatfarmers, whose farms were within the geographical area of the PDO“Ibores Cheese” (whether or not they were producing cheese under thePDO scheme). From the data provided by the Extremadura Departmentof Agriculture and Rural Development (CAYDR, 2007), we selected those

1 Located between longitudes 5◦29′0.56′′W–5◦3′31.05′′W and betweenlatitudes 39◦23′52.63N–39◦45′54.00′′N (reference system: EuropeanDatum 1950 (ED50)).

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Table 1Qualitative and quantitative variables used in the analysis.

Quantitative variables Qualitative variables

Goats Age of the holder <40 yearsKids born 41–50 years

Sheep (ewes) >50 yearsBuildings (m2 per 100 goats) Land Most of the area ownedMilking points Most of the area rented

Litres of milk/goat (l) PDO “Ibores Cheese” Does not belong to the PDODays of milking (days/goat/year) Belongs to the PDO

Total AWUs (annual work units) Type of farm ExtensiveFeedstuff (D ) Semi-intensive

Other expenditure (D ) Development of the herd StablePayments in rented land (D ) Increasing

Total milk (l) DecreasingTotal milk sales (D ) Predominant goat breed SerranaLivestock sales (D ) CrossedSubsidies perceived (D ) Verata-Retinta

Malaguena and/or Murciano-Granadina

Mixed farm Only goatOther species

Electricity Not connected to the gridConnected

Kidding periods per year OneMore than one

Veterinary medical association membership NoYes

Professional agricultural association membership NoYes

Sown forage NoYes

Type of milking Hand milkingMechanical milking

Owns milk tank NoYes

Access to piped water NoYes

Has enclosed paddocks NoYes; fenceYes; stone walls

Owns tractor NoYes

ilk repla

Artificial rearing with m

Specific information was collected on management, together withdata covering family characteristics, labour, livestock size, land use, instal-lations, continuity, recent changes in farming, and the farmer’s opinions.The questionnaire included different questions (quantitative and qualita-tive), that were considered to have the greatest potential to discriminatebetween different types of farms, based on previous studies and a litera-ture review (Castel et al., 2003; Usai et al., 2006; Escribano et al., 2007). Thefinal variables obtained from the questionnaire, their units, and abbrevi-ations when appropriate are listed in Table 1.

The first stage of data analysis consisted of a principal componentanalysis (PCA). This multivariate technique is based on eliminating theredundancy involved in dealing with many variables (Bisquerra, 1989). Itwas used to examine the relationships among the 15 original quantitativevariables (census, production, economic flows, and labour) and to reduce

cer NoYes

their number. Bartlett’s sphericity test and the Kaiser–Meyer–Olkin(KMO) measure of sampling adequacy were applied to test the validityof the sample. The former is used to check that the correlation matrixis close to an identity matrix, i.e., one with all the diagonal elementsunity and the off-diagonal elements null (Visauta, 1998), and the latter tocompare the observed correlation coefficients with the partial correlationcoefficients.

The second stage consisted of a two-step cluster analysis (SPSS, 2006)to classify the farms into homogeneous segments using the principal com-

ponents obtained in the PCA and the 18 qualitative categorical variables.The aim of this technique is to group together those farms which aresimilar to each other but different from others, maximizing intra-grouphomogeneity and inter-group diversity. All analyses were performedusing the statistical package SPSS (v. 15.0).

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Table 2Principal components selected on the basis of the principal component analysis, eigenvalues, the explained and accumulated variances, and squaredmultiple correlation coefficients of the indicators with the different PCs.

Eigenvalue %Variance explained %Variance accumulated Indicators and correlations with the PC

PC 1 3.178 22.702 22.702 Goats 0.859Kids born 0.843Milking points 0.695Total milk (l) 0.678

PC 2 2.654 18.960 41.662 Sheep (ewes) 0.901Livestock sales (D ) 0.841

3

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PC 3 1.554 11.097 52.758PC 4 1.541 11.010 63.769PC 5 1.199 8.566 72.334

. Results

.1. Principal components characterizing the farms

In the first stage, the results of Bartlett’s sphericity testnd the Kaiser–Meyer–Olkin (KMO) measure2 both corre-ponded to good sampling adequacy, thus validating theample variables for the subsequent PCA (Luque, 2000;PSS, 2006).

The PCA yielded five principal components (PCs) thatxplained 72.33% of the variance, which is considered aatisfactory percentage (Hair et al., 1999; Malhotra, 2004).hese five PCs were then interpreted using the varimaxotation of the component matrix. Table 2 gives the prin-ipal components selected on the basis of the PCA, theariance that each explained, and the variables that hadn absolute value of the correlation with the PC greaterhan 0.5. Based on the correlations between the PCs andhe original variables, their interpretation is as follows:

.1.1. Principal component 1: Size of the farmPC 1 explains 22.70% of the variance, and presents very

igh and positive correlation coefficients for the variablesoats and kids. It also has positive correlation coefficientsor the variables milking points and total litres of milk sold.his factor is indicative of the size of the farm, and farmsith high values of this PC have many breeders.

.1.2. Principal component 2: Livestock orientationPC 2 explains 18.96% of the variance, and the variables

ith the greatest positive loadings for this PC are sheep,ivestock sales, and subsidies perceived. It can therefore beonsidered a factor relating to the orientation of the farmsccording to the predominant ruminant species. Higheralues correspond to mixed farms with sheep, and lowero farms that only raise goats.

.1.3. Principal component 3: Physical installationsPC3 explains 11.09% of the variance, and presents high

egative loadings for the variable buildings (m2 of buildings

er 100 goats). It is a factor indicative of a farm’s lack of

nstallations. Farms with high values are those with lessvailability of infrastructure.

2 Kaiser-Meyer-Olkin (KMO) measure: 0.626. Bartlett’s sphericity test:hi-squared 121.492; sig.: 0.018.

Subsidies perceived (D ) 0.792Buildings (m2 per 100 goats) −0.797Litres of milk/goat (l) 0.896Total AWUs (annual work units) 0.816

3.1.4. Principal component 4: ProductivityPC4 can be defined as a “productivity factor”. It explains

11.01% of the variance, and indicates a farm’s average pro-ductivity per goat. The variable with the highest (positive)loading for this factor is milk yield measured in litres pergoat per year.

3.1.5. Principal component 5: Labour managementPC5 explains 8.56% of the variance, and presents a high

and positive loading with the variable Total AWUs (employ-ees working on the farm, in annual work units). The farmswith higher values of this factor are those that use morelabour.

3.2. Establishment of the typology

The two-step cluster analysis showed the optimumnumber of groups as identified by Schwarz’s Bayesiancriterion (SPSS, 2006) to be 3. The original quantitative vari-ables were compared by means of an analysis of variance(ANOVA) according to the groups obtained in the clusteranalysis. The results are given in Table 3. A chi-squared testwas applied to the qualitative variables, and the results arealso given in Table 4. The characteristics defining the threegroups are described in the following.

3.2.1. Group 1: Semi-intensive goat farmsThis group includes 27.89% of the farms surveyed. It is

characterized by farms with small herds, since only 5.9%of the group has more than 350 goats. They are mainlyfarms that do not belong to the PDO, because their pro-duction systems (semi-intensive or intensive) togetherwith the goat breeds (Murciano-Granadina and Malaguena,which are non autochthonous breeds) they have chosenare not allowed under the PDO regulations. Most (70.6%)are semi-intensive farms, with animals spending long peri-ods penned under cover, and although some of the farmarea is forage, this is generally rented land. This is thegroup with most physical installations, since 82.4% of themmilk mechanically, with an average of 5.82 double milk-ing points per farm. Most (58%) have a connection to theelectricity grid.

The kids marketed are the same as in the other groups:9 kg live weight and 45 days of age. However, the produc-tivity per goat is the highest: 312 l of milk per goat per year,with an average of 236 milking days. Another managementcharacteristic that allows them to obtain better returns is

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Table 3Means and significance levels (ANOVA) of the quantitative variables by farm type.

Variables(units)

Group 1 (n = 17) Group 2 (n = 15) Group 3 (n = 29) Total (n = 61) F Significant

Mean SD Mean SD Mean SD Mean SD

Goats 196.9 87.8 470.3 186.2 196.2 101.2 263.8 170.5 27.47 0.000***

Kids born 199.3 116.3 421.5 131.4 180.2 116.5 248.7 157.1 18.21 0.000***

Sheep (ewes) 7.6 26.8 188.9 268.7 184.6 298.3 136.3 255.1 3.22 0.047*

Buildings (m2

per 100goats)

256.5 261.7 113.5 112.9 199.6 147 194.3 184.6 2.54 0.09

Milking points 5.8 4 7.5 4.8 3.3 3.3 5 4.2 6.33 0.003**

Litres ofmilk/goat (l)

312.8 149.2 189 61.2 207.5 79.2 235 112.9 5.47 0.008**

Days of milking(days/goat/year)

236.7 49.1 227.1 40.3 226.6 45.1 229.5 44.4 0.26 0.77

Total AWUs(annual workunits)

1.4 0.6 2 0.8 1.5 0.6 1.6 0.7 3.54 0.036*

Feedstuff (D ) 20,218.9 10,634.6 32,088.4 14,770.2 19,467.7 12,868.2 22,661.2 13,479.4 3.98 0.026*

Otherexpenditure(D )

1889.5 1763.9 4667.3 4665.3 3452 2917 3313.1 3279.4 2.71 0.08

Payments inrented land(D )

730.9 1202.8 6500 6033.2 3717.9 6379.1 3498.6 5607.8 4.32 0.019*

Total milk (l) 58,387.3 43,748.3 76,671.6 29,159.6 35,744.7 24,830.8 52,699 36,171.3 6.42 0.003**

Total milk sales(D )

25,420.6 21,553.9 45,690.8 39,886.9 19,528.1 12,553.7 28,473.7 27,008.4 4.08 0.024*

Livestock sales(D )

9432.3 7525.9 22,699.6 10,861.6 22,285.4 18,778.3 18,770 15,185.3 3.87 0.029*

Subsidiesperceived(D )

4347.9 2478.8 11,866 8271.8 8720.1 8970.6 8825.3 8207.3 1.88 0.17

* p < 0.05.** p < 0.01.

*** p < 0.001.

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7Table 4Frequencies (percentage of farms) and significance level (chi-squared test) of the qualitative variables by farm type.

Group 1 Group 2 Group 3 Total 95% Confidenceinterval

Significant

n = 17 n = 15 n = 29 n = 61

Age of the holder <40 years 23.5 0 17.2 14.8 23.7 5.9 0.12041–50 years 35.3 53.3 62.1 52.5 65.0 40.0>50 years 41.2 46.7 20.7 32.8 44.6 21.0

Land Most of the area owned 29.4 33.3 37.9 34.4 46.3 22.5 0.840Most of the area rented 70.6 66.7 62.1 65.6 77.5 53.7

PDO “Ibores Cheese” Does not belong to the PDO 58.8 60 10.3 36.1 48.2 24.0 0.000***

Belongs to the PDO 41.2 40 89.7 63.9 76.0 51.8Type of farm Extensive 29.4 93.3 89.7 73.8 84.8 62.8 0.000***

Semi-intensive 70.6 6.7 10.3 26.2 37.2 15.2Development of the herd Stable 76.5 0 51.7 45.9 58.4 33.4 0.000***

Increasing 23.5 100 27.6 44.3 56.8 31.8Decreasing 20.7 9.8 17.3 2.3

Predominant goat breed Serrana 0 40 58.6 37.7 49.9 25.5 0.000***

Crossed 17.6 0 31 19.7 29.7 9.7Verata-Retinta 47.1 60 10.3 32.8 44.6 21.0Malaguena and/orMurciano-Granadina

35.3 0 0 9.8 17.3 2.3

Mixed farm Only goat 88.2 40 31 49.2 61.7 36.7 0.001**

Other species 11.8 60 69 50.8 63.3 38.3Electricity Not connected to the grid 52.9 93.3 96.6 83.6 92.9 74.3 0.000***

Connected to the grid 47.1 6.7 3.4 16.4 25.7 7.1Kidding periods per year One 40 60 79.3 64.4 76.4 52.4 0.030*

More than one 60 40 20.7 35.6 47.6 23.6Veterinary medical association

membershipNo 88.2 53.3 37.9 55.7 68.2 43.2 0.000***

Yes 11.8 46.7 62.1 44.3 56.8 31.8Professional agricultural

association membershipNo 70.6 80 41.4 59 71.3 46.7 0.030*

Yes 29.4 20 58.6 41 53.3 28.7Sown forage No 38.5 41.7 83.3 61.2 73.4 49.0 0.008**

Yes 61.5 58.3 16.7 38.8 51.0 26.6Type of milking Hand milking 17.6 13.3 37.9 26.2 37.2 15.2 0.136

Mechanical milking 82.4 86.7 62.1 73.8 84.8 62.8Owns milk tank No 31.3 66.7 62.5 54.5 67.0 42.0 0.082

Yes 68.8 33.3 37.5 45.5 58.0 33.0Access to piped water No 44.4 75 90 75.8 86.5 65.1 0.030*

Yes 55.6 25 10 24.2 34.9 13.5Has enclosed paddocks No 20 15.4 3.8 11.1 19.0 3.2 0.551

Yes; fence 60 61.5 65.4 63 75.1 50.9Yes; stone walls 20 23.1 30.8 25.9 36.9 14.9

Owns tractor No 58.8 73.3 72.4 68.9 80.5 57.3 0.574Yes 41.2 26.7 27.6 31.1 42.7 19.5

Artificial rearing with milk replacer No 85.7 92.3 100 94.4 100 88.6 0.155Yes 14.3 7.7 0 5.6 11.4 0

* p < 0.05.** p < 0.01.

*** p < 0.001.

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that kidding is distributed into various periods during thecourse of the year, so that milk is available throughout theyear, thus getting better prices. The variable that we haveused to obtain this information was “kidding periods peryear”. When the farmers have only one kidding period, itis in autumn season and it means that most of milk pro-duction is during spring. When they organize more thanone kidding season per year this is done for the purposeof producing milk to be marketed during most part of theyear.

The farms employ one full-time worker, who is usuallythe holder, and one part-time worker. Being the group thatuses most family labour, that second worker is usually theholder’s wife or son.

Expenditure on feedstuff is the highest of the threegroups, while land rental payments are much lower. Beingsemi-intensive farms, the rented land used for browsingconsists mainly of small, privately-owned fields or pub-licly owned land, generally close to the farm’s installationswhich are usually located on owned land. Finally, it is nec-essary to emphasize that this group is the one that presentsthe lowest proportion of membership of agrarian or veteri-nary associations.

3.2.2. Group 2: Large, extensive, mixed livestock farmsThis group comprises 15 farms, representing 24.6% of

the sample. They are farms with large goat herds, which arecomplemented with sheep, and occasionally beef cattle orIberian pig.

The average size of the goat herds is 470 head, and, as inthe other groups, the land is mostly rented. Despite not hav-ing any great availability of installations, these farms haveconstructed technically suitable milking sheds. They aremainly extensive farms that need no installations for keep-ing the goats under cover for long periods. In the last fewyears, the holders have made improvements to the instal-lations, and have increased their livestock numbers. Theyraise mainly autochthonous goat breeds such as Serrana,Verata, and Retinta, even though these are less productivethan non-autochthonous breeds. The group’s average pro-duction indicators are: 189 l of milk per goat per year, andmilking period 227 days.

The average number of employees is two, but unlikethe previous group, they are mainly non-family labour,generally temporary workers. The most important expen-diture is on feedstuff purchase which is higher than inGroup 1 despite their being extensive farms. This expen-diture is due to the presence of the other livestock speciesthat require supplements. The land rental payments areconsiderable (D6500). With respect to output, the aver-age annual milk production is not much higher thanin Group 1, whereas there appear greater differences inrevenue from livestock sales and subsidies, again as a con-sequence of the other livestock species present on thesefarms.

3.2.3. Group 3: Extensive, mixed goat-sheep farmsproducing under the PDO

This group represents 47.5% of the farms, most of themdairy farms producing under the PDO scheme. The goatherd size is very similar to Group 1, but 70% are mixed

esearch 97 (2011) 1–11

farms, generally combining goats with a flock of sheep. Thefarms are basically extensive.

This group is the closest to the traditional farming sys-tem. Its main characteristics are small herds with lowproductivity per goat (average of 207 l per goat for 226milking days), and the presence of autochthonous breedsand their crosses. Although, according to the respondents,the size of the herds has remained stable in recent years,actually the number of goats has decreased in 20% of thefarms, and some holders are considering abandoning thegoat farm altogether or moving towards sheep farmingwithout goats. Some 40% of the farms in this group still milkby hand, and in general these farms present the poorestavailability of installations of all three groups (no runningwater, no milk tanks, etc.). Moreover, 96% of these farmshave no connection to the electricity grid.

The labour employed is similar to Group 1 (average 1.5AWUs). With respect to the degree of cooperativism, theholders of this group choose to belong to professional agri-cultural associations, as well as being members of the PDO.

4. Discussion

In the Villuercas-Ibores mountain area, one observesmajor differences between the three types of goat farms,even though they are subject to the same limiting con-ditions with poor exploitable resources. The differencesare particularly evident in their infrastructure, productiv-ity and animal management, labour characteristics, and thebreeds they exploit.

The traditional goat production systems in the areawere mainly extensive, browsing on herbs and shrubs inmountain areas, with low use of feedstuff from outsidethe farm. This type of system was limited to cheesemak-ing for local markets due to poor transport infrastructureand provided reduced income. The situation did not offerany good expectation of development and opportunitiesfor new generations of holders. The improvement of theroad infrastructure in the region in the last twenty yearsand the improvement in the marketing of cheese products,have led to changes from the traditional system describedabove, to a new model of goat farming more intensive withnon autochthonous breeds.

Group 1 – semi-intensive goat farms with non-autochthonous breeds – are the furthest removed fromthe traditional system and they are specialized in highmilk production, with more intensive management in suit-able installations. They have opted to increase their milkproduction, even when this has meant denying them-selves the possibility of marketing their products underthe PDO scheme, the reason being that the price differen-tial between PDO and non-PDO milk does not justify theproduction constraints imposed by the PDO.

The change in traditional browsing systems has hap-pened to all goat systems located in difficult areas withlimited browsing resources, but where the farmers wanted

to ensure milk production, as Usai et al. (2006) found in Sar-dinia. However, these holdings follow the general trend ofintensification that has occurred recently in goat systemsin many parts of the world (Bouwman et al., 2005; Morand-Fehr and Lebbie, 2004; De Rancourt et al., 2006). According

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o Boyazoglu et al. (2005), this intensification is mainlyue to the increasing demand for milk, simplification of

abour, and high land prices, which favour the exploitationf larger farms. This has been the case in Spain since 1986,hen EU policies led to an increase in stocking densities.

n this sense, Castel et al. (2003) argue that milk goat farm-ng in Spain is intensive, except in marginal areas such ashe present study area. This trend constitutes a medium-r long-term risk for these farms which are uncompetitiveue to their location and production characteristics: as they

ntensify their production systems, they also increase theirependence on external resources, thereby limiting theirustainability over time.

Group 2 has chosen to diversify production, raisingoats and sheep at the same time, and increasing the herdize in order to reduce costs (it has the lowest proportionf labour per head at 1 AWU/330 goats-ewes), and therebymproving their economic indicators. The increased live-tock numbers meant a substantial increase in revenuerom CAP subsidies, since until 2003 they were linked tohe number of head.

Farms belonging to Group 3 follow the most traditionalystem of husbandry, raising autochthonous breeds exten-ively. These are the most marginal farms with very fewnstallations. They can be considered as non-competitiveoldings in that their yields (milk, kids and lambs) are the

owest, basically due to inappropriate management prac-ices. Paradoxically, although these farms are producingnder the PDO scheme, their farmholders are not morective, and they are not seeking new tools with which tomprove the marketing of their products). The reality, how-ver, is that most of the modern and technical farms do notroduce under the PDO scheme.

While the PDO is well-suited to traditional systems,arms which become more intensive and exploit non-utochthonous breeds are no longer eligible for the PDO.he fact that milk prices are not significantly higher whenilk is sold under the PDO scheme means that these pro-

ucers feel they would find no advantage in belonging tot.

Whether land is rented or owned plays an importantole in the farm’s provision of infrastructure. Indeed, Gaspart al. (2008) found that rented holdings are more closelyinked to browsing the natural resources available, whileoldings that are run by the owner usually have better

nstallations and implement such improvements as soilmendments, etc.

In the case of the “Villuercas-Ibores” region, it is com-on practice for farms to lease or rent individual plots, inany cases even far apart. As the land is not owned by the

armers, they are reluctant to invest in it. However, in Group, the most technically sophisticated, the farm’s installa-ions were observed to be located on small, holder-ownedlots near urban areas, with the farmers having invested

n well-equipped milking sheds. Furthermore, these “semi-rban” farms have good road connections, which facilitates

he transport of their milk.

With respect to labour, there were significant differ-nces between the semi-intensive (Group 1) and extensivearms. Due to their mixed nature, the latter require lessabour than those of Group 1 which are exclusively rear-

esearch 97 (2011) 1–11 9

ing goats. Although both Groups 2 and 3 are extensiveand mixed, Group 2 is far removed from the smaller andmarginal farms of Group 3 which hence make a less efficientuse of labour. Levels of labour per 100 animals in farmswere 0.77 AWU/100 animals in group 1, 0.44 AWU/100 ingroup 2 and 0.74 AWU/100 in group 3. Those average levelsof labour per 100 animals are similar to those reported byother workers (Nahed et al., 2006; Ruiz et al., 2009) exceptin the Group 2 farms, in which they are closer to otherextensive dehesa farms such as those identified by Gasparet al. (2008). The percentage of family labour is similar inall three types of farm (90%), a figure consistent with thefindings of Ruiz et al. (2009) for certain types of farm.

Considering the technical and management parameters,one can conclude that no group stands out for its manage-ment of production. The main management problem thesefarms face is the concentration of kidding during autumn.The farmers’ main preoccupation is to have grown kids forsale at Christmas (when the greater demand means thatthe kids attain higher market prices), but this objectivehas a negative impact on milk production. The result isgreater milk production in spring, when prices are lower,and scarce production during the rest of the year, with theconsequent problems of supply for the processing indus-try. This situation has also been described in other goatsystems (Ruiz et al., 2008). In our study, only the Group1 farms schedule kidding throughout the year since, dueto their semi-intensive nature, they are less dependent onbrowsing. However, all three farm types need to improvethis management aspect in order to increase their milkproduction and the price obtained per litre.

With respect to other technical parameters, the resultsfor these farms are similar to those reported for othergoat systems in the Mediterranean area. Suckling lasts for45 days, and, after weaning, kids are sold for slaughter. Theuse of artificial rearing with milk replacer is uncommon, aswas also found by Castel et al. (2003) in Andalusian farms.Even so, Group 3 diverges clearly from the other even inthese parameters, since none of its farmers rear artificially,and most of them have no milk tank on the farm, so thatthey have to use their own vehicle daily to transport themilk in cans to community tanks.

The feed requirements are basically satisfied by brows-ing, but since these dairy farms depend on the naturalresources offered by a semi-arid environment with strongseasonal variations, they need to supplement the animalsfeed to ensure good milk production. This is especiallyimportant in the semi-intensive farms of Group 1, sincetheir rearing of non-autochthonous breeds means thattheir largest expense is in purchasing feed. Some farms sowforage, but they belong mainly to Groups 1 and 2, while thefarms in Group 3 are basically dependent on natural forage.

To conclude, we can state that there are some ways ofimprovement, mainly dealing with the seasonality of pro-duction and with the deficient business structure due tothe low investment in infrastructure and technology. Both

problems are a severe constraint on these farms’ productiv-ity and competitiveness in comparison with other regionsand livestock systems.

The strategies to reduce milk production concentrationwould imply a better kidding planning. For example, a

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spring kidding would allow the farmers to sell the milk inJune–November, when milk prices are higher, thus increas-ing the farm’s income. Farmers should adjust accuratelythe number of kid goat produced in this spring kidding,according to grass production forecast. Otherwise, and asthe grass available for grazing during the summer is scarce,production costs could increase significantly.

Another useful tool that could help to improve the busi-ness structure (mainly linked to land tenancy and to theadvanced age of the farmers) is the organization of produc-ers by creating cooperatives. This would allow the farmersa better access to credit and financing or even subsidies.Cooperatives, too, can establish specific education pro-grammes to update the farmers’ professional skills.

5. Conclusions

The present results have shown that most goat farmsin the area still practice a traditional system of husbandry.They have modified or improved neither their technologynor their management practices. Their milk production ishighly concentrated in the periods of greatest abundance ofnatural forage for livestock, which is when the prices theycan obtain are low. The same applies to kid production.With their concentration of kidding seasons, the product ismarketed in the period in which there is greater demandbut also when there is a massive accumulation of supply.While the breeds permitted for production under the PDOare less productive than other non-autochthonous breeds,the main reason for this low productivity is because thefarmers exploiting these breeds have not implemented anyplans of improvements to attain more productive animals.

About a third of the farms surveyed have opted forfarming systems that are incompatible with the PDO reg-ulations, either using unallowed breeds or by not using apurely extensive system of management. Nonetheless, theyare farms which have managed to improve their installa-tions, obtain good levels of production, and increase theirrevenue.

The third option chosen by goat producers in the area isto combine goat herds with other animal species in largerfarms, supplementing the limited production of the goatherd with the output of the other livestock species.

Generally one of the problems presented by most of theholdings in the area is that most of their browsing land isunder lease or rent, thus limiting their possibility of invest-ing in installations.

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